Stop Human Spam

TL;DR

Human spam is harder to block than bot spam. This guide covers techniques like CAPTCHAs, email verification, reputation systems, and content analysis to reduce it. No single method is perfect – a combination works best.

1. Understand the Problem

Unlike bots, humans actively try to bypass security measures. They can solve CAPTCHAs, verify emails, and mimic legitimate users. This means you need more sophisticated techniques than simple spam filters.

2. Implement Strong CAPTCHA Systems

1. Choose a modern CAPTCHA: reCAPTCHA v3 (Google) is a good starting point as it provides a score based on user interaction, rather than requiring explicit challenges for everyone. hCaptcha is another option.
2. Adjust Sensitivity: Configure the sensitivity of your CAPTCHA to balance security and usability. A lower threshold means more users will be challenged, but fewer spam submissions.
3. Invisible reCAPTCHA: Use invisible reCAPTCHA where possible. It runs in the background and only challenges suspicious users.

Example (reCAPTCHA v3 site key setup – this is a simplified illustration; refer to Google’s documentation for full implementation):

<script src="https://www.google.com/recaptcha/api.js" async defer></script>

3. Email Verification

1. Double Opt-in: Require users to confirm their email address by clicking a link in an email sent after registration.
2. Email Age: Flag accounts created with very recently registered email addresses as potentially suspicious.
3. Disposable Email Address (DEA) Blocking: Use services or lists to identify and block registrations from known DEA providers.

4. Reputation Systems

1. IP Address Reputation: Track the reputation of IP addresses based on their activity. Block IPs with a history of spam submissions. Services like AbuseIPDB can help.
2. User Behaviour Analysis: Monitor user behaviour for suspicious patterns (e.g., rapid form submissions, unusual login times).
3. Account Age & Activity: New accounts with little or no activity are more likely to be spammers. Implement restrictions on new account privileges.

5. Content Analysis

1. Keyword Filtering: Identify and block submissions containing common spam keywords (e.g., “free money”, “guaranteed results”). Be careful not to create false positives.
2. URL Blacklists: Block links to known malicious or spam websites.
3. Natural Language Processing (NLP): Use NLP techniques to analyze the content of submissions for characteristics of spam (e.g., poor grammar, irrelevant text). This is more advanced but can be very effective.

Example (simple keyword filtering in Python):

spam_keywords = ["free money", "guaranteed results"]
def check_for_spam(text):
  text = text.lower()
  for keyword in spam_keywords:
    if keyword in text:
      return True
  return False

6. Honeypots

Add hidden fields to your forms that are invisible to humans but will be filled out by bots. If these fields are populated, it’s a strong indication of spam.

7. Rate Limiting

1. Limit Submissions: Restrict the number of submissions allowed from a single IP address or user account within a given timeframe.

8. Manual Review & Reporting

Even with all these measures, some spam will get through. Implement a system for users to report suspicious content and have a team review flagged submissions.

9. cyber security Best Practices

Ensure your website is secure against common vulnerabilities (e.g., SQL injection, cross-site scripting) as compromised accounts can be used for spamming.

10. Combine Techniques

The most effective approach is to use a combination of these techniques. Start with CAPTCHA and email verification, then add reputation systems and content analysis as needed. Regularly monitor your system and adjust your settings based on the results.